@inproceedings{AltherrEdererSchaenzleetal.2017,
  author    = {Altherr, Lena and Ederer, Thorsten and Sch{\"a}nzle, Christian and Lorenz, Ulf and Pelz, Peter F.},
  title     = {Algorithmic system design using scaling and affinity laws},
  series = {Operations Research Proceedings 2015},
  booktitle = {Operations Research Proceedings 2015},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-319-42901-4},
  doi       = {10.1007/978-3-319-42902-1},
  pages     = {605 -- 611},
  year      = {2017},
  abstract  = {Energy-efficient components do not automatically lead to energy-efficient systems. Technical Operations Research (TOR) shifts the focus from the single component to the system as a whole and finds its optimal topology and operating strategy simultaneously. In previous works, we provided a preselected construction kit of suitable components for the algorithm. This approach may give rise to a combinatorial explosion if the preselection cannot be cut down to a reasonable number by human intuition. To reduce the number of discrete decisions, we integrate laws derived from similarity theory into the optimization model. Since the physical characteristics of a production series are similar, it can be described by affinity and scaling laws. Making use of these laws, our construction kit can be modeled more efficiently: Instead of a preselection of components, it now encompasses whole model ranges. This allows us to significantly increase the number of possible set-ups in our model. In this paper, we present how to embed this new formulation into a mixed-integer program and assess the run time via benchmarks. We present our approach on the example of a ventilation system design problem.},
  language  = {en}
}
@inproceedings{SchaenzleAltherrEdereretal.2015,
  author    = {Sch{\"a}nzle, Christian and Altherr, Lena and Ederer, Thorsten and Lorenz, Ulf and Pelz, Peter F.},
  title     = {As good as it can be: Ventilation system design by a combined scaling and discrete optimization method},
  series = {Proceedings of FAN 2015},
  booktitle = {Proceedings of FAN 2015},
  pages     = {1 -- 11},
  year      = {2015},
  abstract  = {The understanding that optimized components do not automatically lead to energy-efficient systems sets the attention from the single component on the entire technical system. At TU Darmstadt, a new field of research named Technical Operations Research (TOR) has its origin. It combines mathematical and technical know-how for the optimal design of technical systems. We illustrate our optimization approach in a case study for the design of a ventilation system with the ambition to minimize the energy consumption for a temporal distribution of diverse load demands. By combining scaling laws with our optimization methods we find the optimal combination of fans and show the advantage of the use of multiple fans.},
  language  = {en}
}
@inproceedings{SchaenzleAltherrEdereretal.2015,
  author    = {Sch{\"a}nzle, Christian and Altherr, Lena and Ederer, Thorsten and Pelz, Peter},
  title     = {TOR - Towards the energetically optimal ventilation system},
  pages     = {1 Seite},
  year      = {2015},
  language  = {en}
}